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27 Jul 2020: WHO REALLY SPOKE WHEN? FINDING SPEAKER TURNS AND IDENTITIES IN BROADCAST NEWS AUDIO. ... S. E. Tranter. May 2006. Automatic speaker segmentation and clustering methods have improved considerably over the last few years in the Broadcast News domain.

7 Oct 2001: This was the lowest overall word error rate in the 1997 DARPA broadcast news evaluation, by a statistically significant margin. ... A new scheme was developed for finding speaker clusters in found speech such as broadcast news.

9 Dec 2006: Who Really Spoke When? Finding Speaker Turns and Identities in Broadcast News Audio. ... For example, speaker models can be built for people who are likely to be in the broadcast (such as prominent politicians or main news anchors and reporters).

20 Feb 2018: likelihood. Otherclassifiers such as SVMs [13] and MLPs [14] have also been used.This classification approach has been used successfully in LVCSRtasks such as meetings [15, 14, 16] and broadcast news ... 17] J.L. Gauvain, L. Lamel, and G. Adda,

22 Nov 2006: This is especially thecase when there is no other additional constraints such as a lan-guage model, e.g. ... Major limitations of this paper are thatexperiments are conducted on artificially corrupted data and as-sume noise stationarity; however, recent

10 Oct 2007: UNSUPERVISED TRAINING FOR MANDARIN BROADCAST NEWS AND CONVERSATIONTRANSCRIPTION. L. Wang, M.J.F. ... Index Terms— Speech Recognition, unsupervised learning. 1. INTRODUCTION. For some tasks, such as Broadcast News (BN) transcription, audiodata can be

1 Mar 2000: That system was constructed using HMMs trained on the Wall Street Journal (WSJ) corpus as a base and then adapted to individual data types of broadcast news data using supervised maximum ... The rest of the paper is arranged as follows. We first give

19 Dec 2006: Front-end CMLLRAs it is useful to compare the uncertainty decoding schemes toapproaches such as CMLLR, CMLLR can be modified to usea GMM front-end selection process. ... Future work will examine real found data, suchas broadcast news, and the application

10 Oct 2007: 3. STT POST PROCESSING. In processing data such as Broadcast News (BN) or Broadcast Con-versations (BCs) for an STT system, the first stage is to segment thedata into homogeneous blocks, ... 12] B. Xiang, L. Nguyen, X. Guo, and D. Xu, “The BBN

1 Mar 2000: That system was constructed using HMMs trained on the Wall Street Journal (WSJ) corpus as a base and then adapted to individual data types of broadcast news data using supervised maximum ... The rest of the paper is arranged as follows. We first give

3 Dec 2008: 1. IntroductionSpeech recognition systems are increasingly being built withfound data such as broadcast news and conversational tele-phone speech recordings. ... Therefore, the use ofMLLRDMT as a testing transform with other DSAT modelswas investigated.

19 May 2005: How-ever such a simple linear normalization scheme may not be pow-erful enough to normalize highly non-homogeneous speech data,such as broadcast news. ... Development ofthe CU-HTK 2004 Broadcast News Transcription System,Summited to ICASSP’05. [10] K.

10 Apr 2000: The rest of the paper is arranged as follows. We first give de-tails of the broadcast news data used, and then describe our workon segment processing (segmentation, classification and ... This corpus will be referred to as BN-train96. A further tranche

9 Dec 2006: WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN BROADCAST NEWS AUDIO. ... For exam-ple, speaker models can be built for people who are likely to be inthe broadcast (such as prominent politicians or main news anchorsand reporters).

16 Jun 2000: A more complex example is to automatically detect repeated events in a database of broadcasts which usually correspond to non-news items such as commercials or jingles. ... Since pre-recorded commercials and jingles are often re-broadcast several times,

8 Mar 2000: For speech transcription problems with widely varying speaker, channel and background conditions, such as broadcast news transcription, it is beneficial to include unsupervised test-data adaptation to individual speakers and data ... M A Siegler,

8 Mar 2000: The 1997 HTK Broadcast News Transcription SystemP.C. Woodland, T. Hain, S.E. ... The rest of the paper is arranged as follows. We first givedetails of the broadcast news data used in the experiments,and briefly describe our work on segment processing

2 Mar 2009: 1. IntroductionSpeech recognition systems are increasingly being built withfound data such as broadcast news and conversational tele-phone speech recordings. ... Therefore, the use ofMLLRDMT as a testing transform with other DSAT modelswas investigated.

22 Jun 2007: UNSUPERVISED TRAINING FOR MANDARIN BROADCAST NEWS AND CONVERSATIONTRANSCRIPTION. L. Wang, M.J.F. ... Index Terms— Speech Recognition, unsupervised learning. 1. INTRODUCTION. For some tasks, such as Broadcast News (BN) transcription, audiodata can be

22 Jun 2007: 3. STT POST PROCESSING. In processing data such as Broadcast News (BN) or Broadcast Con-versations (BCs) for an STT system, the first stage is to segment thedata into homogeneous blocks, ... 12] B. Xiang, L. Nguyen, X. Guo, and D. Xu, “The BBN

10 Oct 2007: F. Gales. Abstract— Large vocabulary speech recognition systems areoften built using found data, such as broadcast news. ... I. INTRODUCTION. A DAPTIVE training [1], [2] has become increasinglypopular as greater use has been made of found data, suchas

22 Feb 2007: Thishas allowed large vocabulary continuous speech recognition(LVCSR) tasks, such as Broadcast News transcription [1],to be addressed. ... Howeverfor tasks such as speech recognition often T > L since thesample rate of the observations is fixed.

11 Jan 2008: 1. INTRODUCTION. Adaptive training [1, 2] has become popular as the use of founddata, such as Broadcast News, has increased. ... It is interesting to compare this lower bound approximationfor recognition to standard iterative approaches such as

2 Mar 2000: The 1996 Hub-4 Broadcast News Transcription development data was used for all the experiments reported in this paper. ... In tasks such as following (potentially unknown) speakers through broadcast news shows, where frame error is more important, the

13 May 2004: Knowing the location of other events such as station jingles,commercials or music can help reveal the broadcast structure and allow information-less portions tobe discarded, hence saving processing time, storage ... as convincing on the Broadcast News

2 Mar 2009: However, inmany applications, such as broadcast news transcription orconversational telephone speech, there is no transcriptionavailable for the test data. ... However, in theory this approach can beapplied to any form of linear transforms, such as

30 May 2007: Thishas allowed large vocabulary continuous speech recognition(LVCSR) tasks, such as Broadcast News transcription [1],to be addressed. ... Sinha,. and S.E. Tranter, “Progress in the CU-HTK Broadcast News tran-scription system,” IEEE Transactions Audio

8 Mar 2000: Thus ‘words’ occurring in broadcast news whichrepresent hesitations in speech, such as uh-huh or hmmm were definedas stop words and finally some common function words which ap-peared to have ... to be made equivalent. A stemming excep-tions list was

23 Apr 2007: F. Gales. Abstract— Large vocabulary speech recognition systems areoften built using found data, such as broadcast news. ... I. INTRODUCTION. A DAPTIVE training [1], [2] has become increasinglypopular as greater use has been made of found data, suchas

23 Dec 2004: 6 Language Modelling and Word Lists. In most speech transcription tasks such as for example dictation or Broadcast News transcriptionlarge amounts of representative text data are available. ... 50000 most frequent words occurring in 204 million words

21 Sep 2007: trained on multistyle data sets such as broadcast news or conversational telephone speech. ... large vocabulary Broadcast News corpus of collected broadcast recordings. 1 Introduction.

26 Jan 2004: The lackof intra-frame correlation has been compensated for with transform schemes such as semi-tiedfull covariance matrices (STC). ... For example HMM based large vocabulary speech recognition systems havedominated the standard evaluation tasks such as

9 Dec 2006: WHO REALLY SPOKE WHEN?FINDING SPEAKER TURNS AND IDENTITIES IN BROADCAST NEWS AUDIO. ... For exam-ple, speaker models can be built for people who are likely to be inthe broadcast (such as prominent politicians or main news anchorsand reporters).

20 Feb 2018: The reviewconcludes with a case study of LVCSR for Broadcast News andConversation transcription in order to illustrate the techniquesdescribed. ... Although these simple HMMs may be ade-quate for small vocabulary and similar limited complexity tasks,

30 Mar 2000: The input data is presented to our HTK transcription system as complete episodes of broadcast news shows and these are first converted to a set of segments for further processing. ... Thus words' occurring in broadcast news which represent hesitations in

19 Mar 2008: The reviewconcludes with a case study of LVCSR for Broadcast News andConversation transcription in order to illustrate the techniquesdescribed. ... Although these simple HMMs may be ade-quate for small vocabulary and similar limited complexity tasks,

9 May 2017: The GMM and DNN will be introduced inChapters2.2.1and2.2.2respectively. There are also other variants such as recurrentneural network for acoustic modelling [80]. ... These differ interms of minimising error at different levels such as sentence, word and

9 Jul 2008: 13110.2.6 MBRL on Broadcast News Mandarin. 131. 10.3 Addressing Alignment Issues. ... This is data that is readily available, such as broadcast news (BN) or broadcastconversation (BC).

23 Feb 2002: stemming; and performance on large scale broadcast news databases, such as those used within the TREC-SDR evaluations is generally poor[8]. ... Firstly some information about broadcast structure including potential locations of commercials and story

27 Oct 2015: Broadcast news transcription (BN) [33, 77] and conversational telephone speech (CTS) [88]. ... detect the beginning and the end of speech events; in a broadcast news transcription system,.

16 Nov 2007: BIC Bayesian information criterion. BN Broadcast news. CER Character error rate. ... limited bandwidth domains, such as broadcast news (BN) and conversational telephone speech.

16 Nov 2007: BN Broadcast News. BW Baum Welch. CDHMM Continuous Density Hidden Markov Model. ... more recent Conversational Telephone Speech (CTS) and Broadcast News (BN) data sets.

10 Jun 2010: such as minimum phone error, the transforms for unsupervised adaptation are still obtained. ... data, such as broadcast news and telephone speech recordings. Such found data often has.

17 Sep 2008: 118. 9.1 Broadcast News transcription system architecture. 126. CHAPTER 1Introduction. Automatic speech recognition (ASR) has improved markedly over the last decade such thatit can be used to transcribe speech in ... as Broadcast News and Toshiba

16 Nov 2007: AF Acoustic factorisation. ASR Automatic speech recognition. BN Broadcast news. CAT Cluster adaptive training. ... instead of dictated speech from 1996 when the broadcast news (BN) task was set up.

16 Feb 2008: are often available as aligned documents, such as news stories, which usually need to. ... alignment render it better able to process widely discrepant languages, such as French,.

18 Dec 2003: 6 Language Modelling and Word Lists. In most speech transcription tasks such as for example dictation or Broadcast News transcriptionlarge amounts of representative text data are available. ... 50000 most frequent words occurring in 204 million words

9 Aug 2005: ta found in the real world such as broadcast news and conversational speech over the telephone. ... for the 1998 NIST Hub-4 Information Extraction (Named Entity) Broadcast News Benchmark.

19 Apr 2000: 5. EXPT. 2 – FINDING NON-NEWS EVENTS. Since pre-recorded commercials and jingles are often re-broadcast several times, the audio corresponding to non-news items such as commercials will often ... The technique has shown to be effective at finding